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The Toll-like receptor family mediates the innate immune system through recognizing the molecular patterns of microorganisms and self-components and leading the synthesis of the inflammatory mediators. We retrospectively examined whether or not genetic variations in toll-like receptor 1 (rs5743551, -7202GQ>A), toll-like receptor 2 (rs7656411, 22215G>T), and toll-like receptor 4 (rs11536889, +3725G>C) affected transplant outcomes in a cohort of 365 patients who underwent unrelated HLA-matched bone marrow transplantation (for hematologic malignancies through the Japan Marrow Donor Program. Only donor toll-like receptor 4 variation significantly improved the survival outcomes. A multivariate analysis showed that the donor toll-like receptor 4 +3725G/G genotype was significantly associated with a better 5-year progression-free survival and a lower 5-year transplant-related mortality than other variations. Furthermore, the donor toll-like receptor 4 +3725G/G genotype was associated with a significantly lower incidence of fatal infections than other variations. The validation study of 502 patients confirmed that the donor toll-like receptor 4 +3725G/G genotype was associated with better survival outcomes. Toll-like receptor4 genotyping in transplant donors may therefore be a useful tool for optimizing donor selection and evaluating pretransplantation risks.
Pubmed ID: 28484092 RIS Download
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A Java based software tool designed to simplify and expedite the process of haplotype analysis by providing a common interface to several tasks relating to such analyses. Haploview currently allows users to examine block structures, generate haplotypes in these blocks, run association tests, and save the data in a number of formats. All functionalities are highly customizable. (entry from Genetic Analysis Software) * LD & haplotype block analysis * haplotype population frequency estimation * single SNP and haplotype association tests * permutation testing for association significance * implementation of Paul de Bakker's Tagger tag SNP selection algorithm. * automatic download of phased genotype data from HapMap * visualization and plotting of PLINK whole genome association results including advanced filtering options Haploview is fully compatible with data dumps from the HapMap project and the Perlegen Genotype Browser. It can analyze thousands of SNPs (tens of thousands in command line mode) in thousands of individuals. Note: Haploview is currently on a development and support freeze. The team is currently looking at a variety of options in order to provide support for the software. Haploview is an open source project hosted by SourceForge. The source can be downloaded at the SourceForge project site.
View all literature mentionsA dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
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